TensorFlow 2.x in the Colaboratory Cloud: An Introduction to Deep Learning on Google’s Cloud Service
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Use TensorFlow 2.x with Google’s Colaboratory (Colab) product that offers a free cloud service for Python programmers. Colab is especially well suited as a platform for TensorFlow 2.x deep learning applications. You will learn Colab’s default install of the most current TensorFlow 2.x along with Colab’s easy access to on-demand GPU hardware acceleration in the cloud for fast execution of deep learning models. This book offers you the opportunity to grasp deep learning in an applied manner with the only requirement being an Internet connection. Everything else—Python, TensorFlow 2.x, GPU support, and Jupyter Notebooks—is provided and ready to go from Colab.
The book begins with an introduction to TensorFlow 2.x and the Google Colab cloud service. You will learn how to provision a workspace on Google Colab and build a simple neural network application. From there you will progress into TensorFlow datasets and building input pipelines in support of modeling and testing. You will find coverage of deep learning classification and regression, with clear code examples showing how to perform each of those functions. Advanced topics covered in the book include convolutional neural networks and recurrent neural networks.
This book contains all the applied math and programming you need to master the content. Examples range from simple to relatively complex when necessary to ensure acquisition of appropriate deep learning concepts and constructs. Examples are carefully explained, concise, accurate, and complete to perfectly complement deep learning skill development. Care is taken to walk you through the foundational principles of deep learning through clear examples written in Python that you can try out and experiment with using Google Colab from the comfort of your own home or office.
What You Will LearnBe familiar with the basic concepts and constructs of applied deep learningCreate machine learning models with clean and reliable Python codeWork with datasets common to deep learning applicationsPrepare data for TensorFlow consumptionTake advantage of Google Colab’s built-in support for deep learningExecute deep learning experiments using a variety of neural network modelsBe able to mount Google Colab directly to your Google Drive accountVisualize training versus test performance to see model fit
Who This Book Is For
Readers who want to learn the highly popular TensorFlow 2.x deep learning platform, those who wish to master deep learning fundamentals that are sometimes skipped over in the rush to be productive, and those looking to build competency with a modern cloud service tool such as Google Colab
ASIN : B08T1P6N9Q
Publisher : Apress; 1st ed. edition (January 13, 2021)
Publication date : January 13, 2021
Language : English
File size : 616 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Sticky notes : On Kindle Scribe
Print length : 351 pages
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3 reviews for TensorFlow 2.x in the Colaboratory Cloud: An Introduction to Deep Learning on Google’s Cloud Service
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Kami –
The book I was waiting for! 🙂
Deep Learning is a complicated subject that is often difficult to explain and implement. In this book, Dr. Paper provides an effective overview of DL basics but also covers advanced topics for real-life implementations of DL and ML systems. If you’re hoping to use TensorFlow 2.0 for deep learning projects, this book is an excellent resource. The topics are developed clearly and in sufficient detail to allow one to master them with minimal effort, and the range of topics covered is exceptional. This is the single best resource I’ve found, and is not only a great way to learn new techniques, but also as a resource to quickly refresh one’s memory on topics when one needs a quick reminder, or some starter code for a new project. Tensorflow 2.0, is a framework that will likely gain an increasing share of the DL framework market, and one won’t find a clearer exposition than this book. I highly recommend it.
wrbm –
Easy introduction to the world of Deep Learning with Practical examples
I’ve been looking into getting in the world of deep learning coming from a data engineering background. This book has presented the best opportunity to do so. I’ve been learning and understating the concepts with good examples and with the right technologies used by big cloud providers such as Google Cloud. I’d recommend this book to anyone with some technical skill and exploring to make the jump into this ML area.
Natale2014 –
Libro sicuramente importante per capire il Deep Learning con Google Cloud Service ma purtroppo stampato male.